cambio climatico1

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TheImplicationsofClimateChangeonPavementPerformanceandDesign

ByQiangLi,LeslieMillsandSueMcNeil

AreportsubmittedtotheUniversityofDelawareUniversityTransportationCenter(UDUTC)

September25,2011


DISCLAIMER:

Thecontentsof this report reflect theviewsof theauthors,whoareresponsible forthe factsandtheaccuracyofthe informationpresented herein. This document is disseminated under thesponsorship of the Department of Transportation UniversityTransportation Centers Program, in the interest of informationexchange. The U.S. Government assumes no liability for thecontentsorusethereof.


TableofContentsAbstract 5Acronyms 6Symbols 81. Introduction............................................................................................................12PROBLEMSTATEMENT....................................................................................................................12BACKGROUND...............................................................................................................................13EnvironmentalEffectsonPavementDesign.........................................................................13ClimateChangeanditsImpact.............................................................................................14

PROJECTOBJECTIVES......................................................................................................................18OVERVIEWOFTHEMETHODOLOGY...................................................................................................19REPORTOUTLINE...........................................................................................................................20

2. EnvironmentalEffectsintheMechanisticEmpiricalPavementDesignGuide(MEPDG) 22INTRODUCTION..............................................................................................................................22Temperature.........................................................................................................................22Precipitation..........................................................................................................................22Freeze/Thaw.........................................................................................................................23

CLIMATICINPUTSINMEPDG...........................................................................................................23GeneralInformation.............................................................................................................24WeatherRelatedDataInput................................................................................................24GroundwaterTableDepthInput..........................................................................................26

MAJOROUTPUTSOFTHEEICM........................................................................................................263. ClimateChangeandVariability...............................................................................28INTRODUCTION..............................................................................................................................28IPCCSPECIALREPORTEMISSIONSSCENARIOS.....................................................................................28CLIMATECHANGEVARIABILITY.........................................................................................................29MAGICC/SCENGENSOFTWARE....................................................................................................32

4. IncorporatingClimateChangeintotheMEPavementDesign..............................35INTRODUCTION..............................................................................................................................35PAVEMENTPERFORMANCEPREDICTIONINMEPDG.............................................................................35FlexiblePavementPerformanceModels..............................................................................36PavementPerformanceModelsforJPCP.............................................................................39PavementPerformanceModelsforCRCP............................................................................41

LOCALCALIBRATIONAPPROACH........................................................................................................42


OverviewoftheMethodology..............................................................................................435. CaseStudyandImplementation.............................................................................46STUDYSITESANDPAVEMENTSTRUCTURES..........................................................................................46HISTORICALCLIMATICDATA.............................................................................................................47TRAFFICINPUTSREQUIREDINMEPDG..............................................................................................49DevelopmentofMEPDGTrafficInputs.................................................................................49WIMDataSourcesandResults.............................................................................................51

MATERIALINPUT............................................................................................................................52CLIMATECHANGEPROJECTIONSANDMEPDGCLIMATEDATAGENERATION.............................................54ClimateSensitivity.................................................................................................................55GeneralCirculationModels(GCMs).....................................................................................55ClimateChangeProjectionResults.......................................................................................55GenerationofHCDDataFilesConsideringClimateChange.................................................57

PAVEMENTPERFORMANCECOMPARISONSANDANALYSIS......................................................................58ComparingPerformanceResults..........................................................................................58

MODELCALIBRATIONTOLOCALCLIMATECHANGECONDITIONS.............................................................63VALIDATION..................................................................................................................................64

6. ConclusionsandRecommendations.......................................................................67CONCLUSIONS...............................................................................................................................67LIMITATIONS.................................................................................................................................67RECOMMENDATIONS......................................................................................................................68

7. References..............................................................................................................69APPENDIXAFormatsoftheIntegratedClimaticModelFiles......................................................74APPENDIXBWeighInMotion(WIM)TrafficResults...................................................................77APPENDIXCFormatsoftheMEPDGTrafficImportFiles.............................................................90APPENDIXDMAGICC/SCENGENClimateChangeProjectionResults...........................................92APPENDIXEPavementPerformanceComparisonResults:BeforeandAfterClimateChange.107


AbstractPavementsaredesignedbasedonhistoricclimaticpatterns,reflectinglocalclimateandincorporatingassumptionsaboutareasonablerangeoftemperaturesandprecipitationlevels.Givenanticipatedclimatechangesandtheinherentuncertaintyassociatedwithsuchchanges,apavementcouldbesubjectedtoverydifferentclimaticconditionsoverthedesignlifeandmightbeinadequatetowithstandfutureclimateforcesthatimposestressesbeyondenvironmentalfactorscurrentlyconsideredinthedesignprocess.Thisresearchexplorestheimpactsofpotentialclimatechangeanditsuncertaintyonpavementperformanceandthereforepavementdesign.Twotoolsareintegratedtosimulatepavementconditionsoveravarietyofscenarios.Thefirsttool,MAGICC/SCENGEN(ModelfortheAssessmentofGreenhousegasInducedClimateChange:AregionalClimateScenarioGenerator),providesestimatesofthemagnitudeofpotentialclimatechangeanditsuncertainty.Thesecondtool,theMechanisticEmpiricalPavementDesignGuide(MEPDG)softwareanalyzesthedeteriorationofpavementperformance.Threeimportantquestionsareaddressed:(1)Howdoespavementperformancedeterioratedifferentlywithclimatechangeanditsuncertainty?(2)Whatistheriskifclimatechangeanditsuncertaintyarenotconsideredinpavementdesign?and(3)Howdopavementdesignersrespondandincorporatethischangeintopavementdesignprocess?Thisresearchdevelopsaframeworktoincorporateclimatechangeeffectsintothemechanisticempiricalbasedpavementdesign.ThreetestsitesintheNorthEasternUnitedStatesarestudiedandtheframeworkisapplied.Itdemonstratesthattheframeworkisarobustandeffectivewaytointegrateclimatechangeintopavementdesignasanadaptationstrategy.


AcronymsT2xClimateSensitivityA1familyofemissionsscenariosincludingA1F1fossilintensive,A1Tnonfossilenergy

sources,andA1Bbalancedacrossallsources.AADTTAnnualAverageDailyTruckTrafficAASHTOAmericanAssociationofStateHighwayandTransportationOfficialsACAsphaltconcreteAMDTTAverageMonthlyDailyTruckTrafficAOGCMatmosphere/oceanglobalclimatemodeAVCAutomatedvehiclecountsB1andB2familiesofemissionscenariosCDFClassDistributionFactorCGCM3CanadianCentreforClimateModelingCRCPContinuouslyreinforcedconcretepavementECHAM5/MPIOMMaxPlanckInstituteforMeteorology(Germany)EICMEnhancedIntegratedClimaticModelGBGranularbaseGCMGeneralCirculationModelGFDLCM2.0andCM2.1GeophysicalFluidDynamicsLaboratoryClimateModelsGHGGreenhousegasGMTGlobalMeanTemperatureGPSGlobalPositioningSystemGSunboundgranularsubbaseHadCM3andHadGEM1HadleyCentreforClimatePredictionandResearch(UnitedKingdom)HATTHourlyAveragetrucktrafficforonehourtimeperiodHCDfileextensionforhourlyclimaticdatabasefilesusedbyMEPDGHMAHotmixasphaltICMfileextensionforclimatefilesgeneratedbyMEPDGIPCCIntergovernmentalPanelonClimateChangeIPSL_CM4InstitutePierreSimonLaplace(France)ClimateModelIRIInternationalRoughnessIndex


JPCPJointedplainconcretepavementLTPPLongtermpavementperformanceprogramMAGICC/SCENGENModelfortheAssessmentofGreenhousegasInducedClimateChange:A

regionalClimateScenarioGeneratorMEPDGMechanisticEmpiricalPavementDesignGuideMIROC3.2CenterforClimateSystemResearch(Japan)(mediumresolution)MRICGCM2.3.2MeteorologicalResearchInstitute(Japan))MSLPMeanSeaLevelPressureNCARCCSMNationalCenterforAtmosphericResearchCCSMNCDCNationalClimaticDataCenterNFSNonfrostsusceptiblePCCPortlandCementConcreteSRESSpecialReportonEmissionsScenariosSSSandsoilTBBoundtreatedbaseTMGTrafficMonitoringGuideTMIThornwaiteMoistureIndexTRBTransportationResearchBoardUKCIPUnitedKingdomClimateImpactsProgrammeWIMWeighinmotion


Symbolsa, b, c=calibrationconstantsai,bj,cj=regressioncoefficientsAge=Ageafterconstruction,yearsAge=pavementageinyearsBC=Totalareaofblockcracking(low,medium,andhighseveritylevels),percentoftotal

lanearea,%CthroughC=calibrationconstants C, C=calibrationconstantsCDFj=ClassdistributionfactorforvehicleclassjCidefaultvalueofCiCOV =Rutdepthcoefficientofvariation,percentDE Differentialdeformationenergyaccumulatedduringmonthi.D=accumulatedfatiguedamageattheendofimonthlyincrementdistressestimateddistressusingdefaultcalibrationfactorsE=StiffnessofthematerialEROD=Base/subbaseerodibilityfactorE ElasticityoffactorCifortheassociateddistressconditionFault=Meanjointfaultingattheendofmonthm,in.FAULTMAX Maximummeantransversejointfaultingformonthi,inFC=Totalareaoffatiguecracking(low,medium,andhighseveritylevels),percentofwheel

patharea,%FD=totalfatiguedamageFenv=compositeenvironmentaleffectsadjustmentfactor,FF=adjustmentfactorforfrozenconditionFI=Averageannualfreezingindex.FR=adjustmentfactorforrecoveringconditionsFR=Basefreezingindexdefinedaspercentageoftimethetopbasetemperatureisbelow

freezing(32temperatures.FU=unboundlayermodulusadjustmentfactorforunfrozenconditions


h=Thicknessoflayer/sublayerh=Thicknessofsublayeri.HDFi=Hourlydistributionfactorforithonehourtimeperiodi=age(accountsforchangeinPCCmodulusrapture,layerbondcondition,deteriorationof

shoulderLoadTransferEfficiency)IRI=IRImeasuredwithinsixmonthsafterconstruction,m/kmj=month(accountsforchangeinbaseandeffectivedynamicmodulusofsubgradereaction)k=axletypek, k, k=Laboratoryregressioncoefficientsl=loadlevel(incrementalloadforeachaxletype)LC=Mediumandhighseveritysealedlongitudinalcracksoutsidethewheelpath,

m/km.LC=Mediumandhighseveritysealedlongitudinalcracksoutsidethewheelpath,

m/kmm=temperaturedifferenceMAFi=MonthlyadjustmentfactorformonthiMj=changeinsmoothnessduetomaintenanceactivitiesMR=UnboundmaterialadjustmentfactorMR=PCCmodulusofraptureatagei,psiN=NumberofloadrepetitionsN=Numberoftrafficrepetitionsn=trafficpathN=NumberofrepetitionstofatiguecrackingN,,,=allowablenumberofloadapplicationsatconditioni, j, k, l, m, nN,,,=allowablenumberofloadapplicationsatconditioni, j, k, l, m, n.n,,,=appliednumberofloadapplicationsatconditioni, j, k, l, m, nnsublayers=numberofsublayersP=Areaofhighseveritypatches,percentoftotallanearea,%PATCH=pavementsurfaceareawithflexibleandrigidpatching(allseverities),percentPATCH=percentagepavementsurfacewithpatching(MHseverityflexibleandrigid)P.=Percentpassingthee0.02mmsieveP.=Percentpassingthe0.075mmsieve


P=Percentsubgradepassing#200sieveP=percentsubgradematerialpassingthe0.075mmsieve.PD=pavementpermanentdeformationPI=PlasticityindexPO=totalpredictednumberofpunchoutspermileattheendofimonthlyincrementPUNCH=numberofmediumandhighseveritypunchouts/kmP=Overburdenonsubgrade,lbR=Averageannualrainfall,mmR=Standarddeviationinthemonthlyrainfall,mmRF=ReductionfactorduetothawingRR=RecoveryratioS=degreeofsaturationS(t)=pavementsmoothnessataspecifictimetS0=initialsmoothnessimmediatelyafterconstructionSD(t)=changeofsmoothnessduetotheithdistressatagiventimetintheanalysisperiod(i=1

ton)SD=Standarddeviationoftherutdepth,mm.SDP(%)StandarddeviationofthepercentagechangeinprecipitationSDT(%)StandarddeviationoftemperatureSequil=degreeofsaturationatequilibriumSF=sitefactorSF=sitefactorSj=changeinsmoothnessduetositefactors(subgradeandage)SLR(cm)sealevelriseSopt=degreeofsaturationatoptimumconditionsSPALL=percentageofjointswithspalling(allseverities)T=Mixtemperature(degF)TC=percentageofslabswithtransversecracking(allseverities)TC=numberofmediumandhightransversecracks/kmTC=Averagespacingofhighseveritytransversecracks,mTC=Totallengthoftransversecracks(low,medium,andhighseveritylevels),m/km


TFAULT=totaljointfaultingcumulatedperkm,mmV=airvoids(%)V=effectivebindercontent(%)WetDays=Averageannualnumberofwetdays(greaterthan0.1inrainfall).

=Calibrationfactorfortheunboundgranularandsubgradematerials,,=Calibrationparameters,,=Calibrationfactorsfortheasphaltmixturesrutmodel=Permanentdeformationforthelayer/sublayer MaximummeanmonthlyslabcornerupwarddeflectionPCCduetotemperature

curlingandmoisturewarping,,=Materialproperties,,.=Averageverticalresilientstraininthelayer/sublayerasobtainedfromthe

primaryresponsemodel=Accumulatedpermanentstrain =Totalplasticstraininsublayeri=Resilientstrain=Resilientstrainimposedinlaboratorytesttoobtainmaterialproperties

=Tensilestrainatthecriticallocation,,,=appliedstressatconditioni, j, k, l, m, nCichangeinthefactorCidistresschangeintheestimateddistressassociatedwithachangeinthefactorCiFault=Incrementalchange(monthly)inmeantransversejointfaultingduringmonthi,in.P(%)PercentagechangeinprecipitationT(C)Changeintemperaturesat=saturatedvolumetricwatercontentw=volumetricwatercontent


1. IntroductionProblemStatementPavementstructuresrepresentasignificantinfrastructureinvestmentthatiscriticaltothewellbeing,growthandexpansionofanygeographiclocation.Assuchpavementsareexpectedtobedurableandresilient,andtoperformsatisfactorilythroughouttheirservicelives.Indesigningdurablepavements,severalfactorsareassessedandonesuchprimaryfactoristheclimateoftheproposedhighwaylocation.Climateservesasanessentialinputinpavementdesignanddependingonitsvariabilitycanhavesignificantimpactonpavementperformance.Climatedataforaparticularregioninwhichahighwayislocatedprovidesengineerswithusefulinformationwhendecidingonthecombinationofpavementlayersandmaterialsthatcanwithstandtheelementsoftheenvironmentpeculiartothatregionandperformadequatelyinthefaceofadverseweatherconditions.Climaticindicatorsalsoprovideanexpectationastothetypeandextentofclimateinduceddeteriorationthatthehighwayissusceptibleto.Pavementsaredesignedbasedontypicalhistoricclimaticpatterns,reflectinglocalclimateandincorporatingassumptionsaboutareasonablerangeoftemperatureandprecipitationlevels.Assuchchangesinglobalandmorespecificallyregionalclimatehavethepotentialtoaffectpavementdesignandsubsequentpavementperformanceonceitisputinservice.AccordingtotheIntergovernmentalPanelonClimateChange(IPCC),warmingoftheearthsclimatesystemisunequivocalandmostoftheobservedincreaseisduelikelytoanincreaseinanthropogenicgreenhousegasemissions(IPCC,2007a).Itisprojectedfurtherthatprofoundconsequenceswilloccurtohumanlifeaswellasnaturalandbuiltsystemsifthistrendinanthropogenicclimatechangeweretocontinueunabated.Suchsystemsincludecivilinfrastructuresystems,meaninganysignificantfuturechangeinclimatepertainingtotemperature,precipitationorsealevelrisewillonlyservetocreateadverseeffectsforthesesystems.However,inallthesesystemsthereisuncertaintyasstudiesofclimatechangedonotknowtheexactamountorrateofchangeduetocomplexitiesintheclimatesystemandinthemodelingprocess(Foley,2010).Asaresult,translatingthisuncertaintytothedesignandperformanceofcivilinfrastructuresystemsischallenging.Thereisasharpdivideinthewayclimatescientistsandpavementdesignersanalyzesystemsintheirrespectivedisciplines.Climatescientistsdescribethefutureinprobabilistictermswithaportfolioofplausiblescenariosandoutcomesthatarerefinedasnewknowledgebecomesavailable,whereaspavementprofessionalstendtofocusonknownsandworkwiththebestavailabledata(TransportationResearchBoard,2008).Althoughcurrentpavementdesignstandardsarerobustandconservativeinmanyoccasions,theyneedtobeevaluatedinlightofchangingenvironmentalfactorsrecognizinguncertainty.Inadditionpavementengineershavetodeterminewhethertheirsystemsareadequatetowithstandclimateforcesthatarebeyondenvironmentalfactorscurrentlyconsideredinthedesignprocess.Thisresearchexploreshowtheuncertaintyassociatedwithclimatechangeaffectsthedesignofpavementsandinfluencestheirperformanceafterconstruction.Presently,themajorityofresearchconductedisbasedonanaveragechangeofenvironmentalfactorswithout


consideringtheuncertaintyofthechange.Thisresearchrepresentsadisconnectbetweenknowledgeandactualconditionssincethescienceofclimatechangeischaracterizedbylimitationsastotheextentandmagnitudeofthechangethatwilloccur.Theresearchthereforeseekstoexplorehowuncertaintyasappliedtoclimatechangecouldaffectthedesignofpavementsandinfluencetheirperformanceafterconstruction.Questionslikehowpavementperformancedeterioratesdifferentlywithclimatechangeanditsuncertainty,whatistheriskifclimatechangeanditsuncertaintyarenotconsideredinpavementdesignandhowdopavementdesignersrespondandincorporatethischangeintothepavementdesignprocess?BackgroundEnvironmentalEffectsonPavementDesignEnvironmentalconditionshavesignificantimpactonpavementdesignandperformance.Theseconditionsarerepresentedastheeffectsofweatherandclimateonthestrength,durabilityandloadbearingcapacityofthepavement.Inessence,theyimpactthestructuralandfunctionalintegrityofanyhighway.Pavementsofalltypesaresusceptibletoconditionswithintheenvironmentandeachhasitsuniquewayofrespondingtoaharshenvironmentorclimate.Environmentalconditions,incombinationwithfactorssuchastrafficrelatedloads,constructionmethods,constituentlayermaterialsandmaintenanceandrehabilitationregimensarekeyvariablesintheassessmentofpavementperformance.TheinteractionbetweenthesevariablesandtheireffectonpavementperformanceisshowninFigure1.1(Haasetal,2004).

Figure1.1Factorsaffectingroadperformance(Haasetal,2004)


Notableenvironmentalfactorsdiscussedintheliteratureincludetemperature,precipitation,subsurfacemoistureandfreezethawcycles.Generallythesefactorsleadtodistressformation,whichcontributestopavementdeteriorationandultimatefailureifleftunchecked.Theeffectoftemperatureonpavementsprimarilyresultsinthermalcrackingandpavementdistortioncomprisingrutting,shovingandcorrugation(Baladi,1990).Precipitationischaracterizedbyitsintensityanddurationandaffectstheamountofwaterinfiltratingthepavementsurfaceandtheamountofmoisturewithinthepavementsection.Anexampleofadistresscausedbysustainedprecipitationispumpinginrigidpavements(ERESConsultantsInc,1987,YoderandWitzcak,1979).Subsurfacemoistureisamajorcontributortothegrowthoficelensesbeneathpavementsinwetfreezeregionsanddirectlyinfluencestheamountandrateoffrostheave(Moulton,1980).Moisturerelatedpavementdistressesand/orfailuresarecharacterizedbyexcessivedeflection,cracking,reducedloadbearingcapacityandconcretedeteriorationduetodurabilitycracking(Carpenteretal,1981).Freezethawcyclesareassociatedwithaccumulatediceunderneaththepavementsurfaceandleadtotheformationofvoidsandtensilestrainatthesurfaceofthepavement(Haasetal,2004).Tocounterdistressformationduetoenvironmentalfactors,atthehighwaydesignstageengineersexamineyearsofclimaterecordsforthegeographicareawherethehighwayistobelocatedandselectpavementstructuresandmaterialsthatwillperformwellunderthestatedclimaticconditions.Climateinduceddeteriorationpatternsofexistinghighwaysarestudiedandusedasinputfornewpavementdesigns.Laboratorytestsarethenruntodeterminehowproposedstructureswillperformunderworstcaseenvironmentalconditions.Thislevelofdetailisalsoadoptedduringtheconstructionphasewherecontractorsusemethodsthatminimizetheeffectoftheenvironmentonconstructedhighways.ClimateChangeanditsImpactClimateattheglobal,regionalorlocallevelissubjecttochangeperiodicallyduetonaturalandmanmadefactors.Inallcases,changesinclimatearegenerallyunpredictableandclimatologiststakeaperiodoftime,onaverage50years,toestablishtrendsforaparticularjurisdiction.However,sincethesecondhalfoflastcenturyclimatesciencehasobservedsignificantextremeclimaticeventsthattendtosuggestdeparturesfromeventsusuallyobservedinthepast.Giventhatthesedeparturesareattributedtoanincreaseinhumanactivitiesthataffectclimate,evenmoreprofoundclimaticeventsareprojectedshouldthesehumanactivitiescontinueunchecked(IPCC,1990).Iftheseprojectionsprovetoberight,bothnaturalandbuiltsystemswillbeaffectedandthismakespotentialclimatechangeaphenomenonworthinvestigating.OverviewofGlobalClimateChangeAprimaryingredientthatservesasatriggerforclimatechangeisthegreenhousegaseffect.Greenhousegasesaccumulateintheatmospherefromnaturalormanmadesourcesandcomprisegasessuchaswatervapor,carbondioxide,methane,nitrousoxidesandozone.Oncetheyaccumulateintheatmosphere,thesegasestraplongwaveterrestrialradiationandaffectitsbalancewithshortwavesolarradiation.Studieshaveshownthatoverthepastcentury,anthropogenicsourcesofgreenhousegasemissionshaveincreasedsubstantiallysincepreindustrialtimes,whichhasmadetheimpactofthegreenhouseeffectgreaterthanitshouldbe


andhasledtoadditionalwarmingoftheEarthssurface(IPCC,1990).Furtherinvestigationintoanthropogenicinducedclimatechangerevealedthathumanactivitiessuchasfossilfueluse,landusechangeandagriculturearelikelytohaveproducedapositiveradiativeforcingofclimate,tendingtowarmtheearthssurfaceandtriggeringotherchangesinclimate(IPCC,1995).Someofthesechangeshavepresentlybeenobservedwhereasothershavebeenprojectedtooccurinfuture.Amongthoseobservedpresentlyareriseinglobalaveragesealevel,adecreaseintheextentoficeandsnowcoverandforthepastfourdecades,atemperatureriseinthelowesteightkilometersoftheatmosphere.Forfuturechanges,globalmodelsimulationsandavarietyofscenariospredictanincreaseinmeanprecipitationwithmoreintenseprecipitationevents,highermaximumtemperaturesandmorehotdaysovernearlyalllandareas,higherminimumtemperaturesandfewercoldandfrostdaysovernearlyalllandareas,increasedtropicalcycloneintensitiesandincreasedsummercontinentaldryingwithassociatedriskofdrought(IPCC,2001,IPCC,2007).Inallthesereports,theauthorscitelimitationswithregardstomodeluncertainty,futureemissionsanduncertaintiesinclimatevariability.Theseareintendedtobereducedasmoredataandscientificunderstandingofyettobeexplainedclimatephenomenabecomeavailable.ImpactsofClimateChangeonTransportationTheTransportationResearchBoards(TRB)SpecialReport290(TransportationResearchBoard,2008)catalogsthepotentialimpactsofclimatechangeontransportationintheUnitedStates.Fromthereport,climatechangewillhavesignificantimpactsonthewaytransportationprofessionalsplan,design,construct,operateandmaintaininfrastructure.Itfurtherstatesthatimpactsfromincreasesinseveraltypesofweatherandclimateextremeswillvarybymodeoftransportation,geographicallocationandconditionoftheinfrastructure.Thereportthenlistsfiveclimatechangesofparticularimportancetotransportationasincreasesinveryhotdaysandheatwaves,increasesinArctictemperatures,risingsealevels,increasesinintenseprecipitationeventsandincreasesinhurricaneintensity.Basedonthese,thepotentiallygreatestimpactofclimatechangeonNorthAmericastransportationsystemisidentifiedasfloodingofcoastalroads,railways,transitsystemsandrunwaysasaresultofglobalsealevelrise,coupledwithstormsurgesandexacerbatedinsomelocationsbylandsubsidence.Table1.1,exertedfromtheTRBSpecialReport290showspotentialimpactstoUStransportationduetothefiveprojectedchangesinclimatelistedabove.AnexampleofadetailedstudyontheimpactofclimatechangeontransportationattheregionallevelistheUnitedStatesGulfCoast(U.S.ClimateChangeScienceProgram,2008).ThestudyidentifiedfourkeyclimatedriversintheGulfregionasrisingtemperatures,changingprecipitationpatterns,risingsealevelsandincreasingstormintensity.Findingsfromthestudyshowedthattheregionshighways,pipelines,ports,raillinesandairportswouldsufferseveredamageshouldextremechangesinregionalclimateoccur.ThesewouldcausemajorandminordisruptionstotheprovisionoftransportationserviceswithintheGulfandadverselyaffectthequalityoflifeintheregion.


Table1.1:PotentialClimateChangesandIllustrativeImpactsonTransportation(TransportationResearchBoard,2008)PotentialClimateChange ExamplesofImpactson

OperationsExamplesofImpactsonInfrastructure

Increasesinveryhotdaysandheatwaves

Impactonliftoffloadlimitsathighaltitudeorhotweatherairportswithinsufficientrunwaylengths;limitsonconstructionactivityduetohealthandsafetyconcerns

Thermalexpansionofbridgeexpansionjoints;railtrackdeformities

IncreasesinArctictemperatures

Longeroceantransportseasonandmoreicefreeportsinnorthernregions;possibleavailabilityofanorthernsearouteoranorthwestpassage

Thawingofpermafrost,causingsubsidenceofrailbeds,bridgesupports,pipelinesandrunwayfoundations

Risingsealevels,combinedwithstormsurges

Morefrequentinterruptionstocoastalandlowlyingroadwaytravelandrailserviceduetostormsurges;moreseverestormsurgesrequiringevacuationorchangesindevelopmentplans;potentialforclosureofairportsincoastalzones

Inundationofraillinesandairportrunwaysincoastalareas,morefrequentorseverefloodingofundergroundtunnelsandlowlyinginfrastructure;erosionofbridgesupports;reducedclearanceunderbridges;changesinharborandportfacilitiestocopewithtides

Increasesinintenseprecipitationevents

Increasesinweatherrelateddelaysandtrafficdisruptions;increasedfloodingofevacuationroutes;increasesinairlinedelays

Increasesinfloodingofraillines,subterraneantunnelsandrunways;damagestorailbedsupportstructures;damagestopipes

Morefrequentstronghurricanes(Category45)

Morefrequentinterruptionstoairservice;morefrequentandpotentiallymoreextensiveemergencyevacuations;moredebrisonroadsandraillines,interruptingtravel

Greaterprobabilityofinfrastructurefailures;increasedthreattostabilityofbridgedecks;adverseimpactsonharborinfrastructurefromwavesandstormsurges.

Inrelatedstudies,researchershaveexpandedtheimpactofclimatechangeontransportationbeyondinfrastructureandoperationstoincludeitsinfluenceondecisionmakingprocessesandconsequently,policyformulation(TransportationResearchBoard,2008,U.S.ClimateChange


ScienceProgram,2008,TransportationResearchBoard,2009).Forexample,TRBSpecialReport299(TransportationResearchBoard,2009)laysoutadecisionframeworkfortransportationprofessionalstouseinaddressingimpactsofclimatechangeonU.S.transportationinfrastructureandinvolvesthefollowingsteps:

1. Assesshowclimatechangesarelikelytoaffectvariousregionsofthecountryandmodesoftransportation.

2. Makeaninventoryoftransportationinfrastructureessentialformaintainingnetworkperformanceinlightofclimatechangeprojectionstodeterminewhether,when,andwheretheimpactscouldbeconsequential.

3. Analyzeadaptationoptionstoassessthetradeoffsbetweenmakingtheinfrastructuremorerobustandthecostsinvolved.Considermonitoringasanoption.

4. Determineinvestmentpriorities,takingintoconsiderationthecriticalityofinfrastructurecomponentsaswellasopportunitiesformultiplebenefits(e.g.,congestionrelief,removalofevacuationroutebottlenecks).

5. Developandimplementaprogramofadaptationstrategiesfornearandlongtermscenarios.PeriodicallyassesstheeffectivenessofadaptationstrategiesandrepeatSteps1through5.

Otherstudieshave looked intohow transportationplanningvisvis landuseplanningcouldminimize the effect of climate change and how improvements in theUS fuel economy andintroduction of alternative fuels could affect total transportation greenhouse gas emissions.What serves as a recurrent theme in amajority of these studies is the vulnerability of thenationstransportationsectorwithincreasingriskofclimatechange. ImpactsofClimateChangeonPavementsAllpavementtypesaresusceptibletodeteriorationgivenapotentialchangeinclimateoccurs(Meyeretal,2010,MeyerandWiegel,2011).Fromdistressesatthesurfacetocollapseofconstituentlayers,pavementsarelikelytoundergodrasticdeformationshouldtheyexperienceextremesinweatherorclimate.Undernormalclimatechangeconditions,rigidpavementssufferfromdistresseslikescaling,Dcracking,pumping,faulting,curling,cornercrackingandpunchouts.Flexiblepavementsunderthesameconditionsareaffectedbybleeding,weathering,bumps,rutting,depressions,potholes,longitudinalandtransversecracking(Baladi,1990).Someofthesedistressesareformedincombinationwithtrafficloadsandormaterialdefects.Ifextremeclimatechangesweretooccur,thesedistresseswillclearlybeexacerbatedandnewdistressesmaybeformed.Listedaresomeofthepotentialproblemspavementswillfaceunderextremeclimatescenarios(TransportationResearchBoard,2008).

Longperiodsofextremeheatmayleadtothermalexpansionofpavedsurfacesandmaycompromiseflexiblepavementintegritye.g.softenasphalt,increaseruttingfromtrafficandcausemigrationofliquidasphalt.

IncreasesinArctictemperaturescouldcausepermafrosttothawandleadto


subsidenceofroadsandshorterseasonsforiceroads,whosefrozenbedstruckstakeadvantageoftocarryheavierloadsduringwinter.

Risingsealevelscombinedwithstormsurgescouldinundateroadsoreroderoadbaseswhereasincreasesinintenseprecipitationeventswouldcauseroadwaystofloodandleadtoincreasesinroadwashouts.

SpecificstudiesundertakenforpavementsinSouthernCanada(Millsetal,2007)analyzedtheeffectsofpotentialclimatechangeonpavementinfrastructure.Twocasestudieswereanalyzedbasedonmidcenturyclimatepredictedbyselectedglobalclimatemodels.Thefirststudyexamineddeteriorationrelevantclimateindicatorsandshowedthatlowtemperaturecrackingwouldbelessproblematic,pavementstructureswouldfreezelaterandthawearlierwithshorterfreezeseasonlengthsandpotentialruttingcouldoccurforinservicepavementsexperiencinghightemperatures.ThesecondstudyusedtheMechanicalEmpiricalPavementDesignGuide(AppliedResearchAssociatesInc,2004a)toassesstheimpactofclimatechange,trafficloadsandthestructuralandmaterialpropertiesofthepavementonincrementalandterminalpavementdeteriorationandperformance.Resultsshowedruttingandlongitudinalandalligatorcrackingwouldbeexacerbatedbyclimatechange.InstudiesundertakenfortheGulfCoastoftheUnitedStates(U.S.ClimateChangeScienceProgram,2008),researchersobservedthatkeypotentialimpactsonthehighwaynetworkwouldbelargelyduetosealevelriseandstormsurge.Temperatureandintenseprecipitationwouldalsohavesomeimpactsbutwouldbelowercomparedtothoseresultingfromsealevelrise.Extremeheatisexpectedtoincreasehighwaymaintenanceandconstructioncostsassomepavementmaterialswilldegradefasterduetohighertemperatures.Intenseprecipitationeventswillleadtoincreaseinaccidents,washouts,flooding,landslides,andcauseunduestressforstormwatermanagementinfrastructure.Sealevelriseandstormsurgewouldaffecthighwaysinlowlyingareasoftheregionandwouldcauseinundation.Prolongedinundationcanleadtolongtermweakeningofpavements.Asstatedabove,bothgeneralandspecificstudiesdescribingtheimpactsofclimatechangeindicatethatpavementswillbeadverselyaffectedbythisphenomenon.Itisimperativethereforeforallstakeholderstoresearchwaystopreservepavementsandminimizetheseimpactssoastoreducelossesthatwouldbeincurredintheeventofunexpectedchangesinclimate.ProjectObjectivesGivenanticipatedclimatechangesandtheinherentuncertaintyassociatedwithsuchchanges,apavementcouldbesubjectedtoverydifferentclimaticconditionsoveritsdesignlife.Theobjectiveofthisresearchistoexploretheimpactsofpotentialclimatechangeanditsuncertaintyonpavementperformancedeteriorationandthereforepavementdesign.Therearethreefundamentalsourcesofuncertaintytobeaddressed:

Greenhouseandothergasemissions:TheIPCCSpecialReportEmissionScenarios(SRES)project(IPCC,2011)averywiderangeofemissionsofkeygreenhousegases(GHG);


Climatesensitivity:Howmuchglobalmeantemperature(GMT)willwarmforaCO2doublinghastraditionallybeenthoughttobebetween1.5to4.50C;

Patternsofregionalchange:Thisthirdsourceofuncertaintyconcernsrelativeregionalchangesintemperatureandprecipitation.Bothglobaltemperaturesandprecipitationwillrise,butsomeareaswillwarmmorethanothersandsomeareasreceiveincreasedprecipitationwhileothersfacedecreases.

Toaccomplishthismainobjective,thefollowingsubobjectivesareexplored: Reviewofthepotentialimpactofclimatechangeonpavementperformance Explorationofclimatechangescenariosanduncertaintiesusingthe

MAGICC/SCENGENtool(Wigley,2008) Simulationofpavementperformancedeteriorationovertimeforaselectionof

siteswithvariousclimatechangelevelsandpavementstructures Analysistoassessthesignificanceofclimatechangepavementperformance Developmentofguidanceonwhenandhowtointegrateclimatechangeinto

pavementdesignasanadaptionstrategy.OverviewoftheMethodologyTheresearchfocusesonhowpotentialclimatechangeintheNorthEasternpartoftheUnitedStatescouldaffectroadpavementsatdifferentlocationswithintheregion.Threelocationswerechosen,oneineachofthefollowingstates:Delaware,NewJerseyandConnecticut.Thepavementtypesselectedwerejointedplainconcretepavement(JPCP),continuouslyreinforcedconcretepavement(CRCP),acompositepavementandanasphaltconcretepavement.UsingdatafromtheLongTermPavementPerformance(LTPP)database(FHWA,2010)andtheMechanisticEmpiricalPavementDesignGuide(MEPDG)(TRB,2010)asadesigntool,pavementsweredesignedwithsimilarinsitustructurestosimulatehowtheywouldperformovertimeshouldchangesinclimateoccur.Indeterminingclimaticfactorstobeconsideredintheresearch,areviewofpastresearchonclimaticimpactsonpavementperformancewasdoneandnarroweddowntoclimaticfactorsofrelevancetopavementswithineachoftheselectedlocations.Ofkeyinterestishowuncertaintyinprojectingfuturechangesinthesefactorscanbecharacterized.Toexploreuncertainty,climatemodelsandclimatechangescenariosdevelopedbasedonresearchbytheIntergovernmentalPanelandUnitedKingdomClimateImpactsProgramme(UKCIP)(DepartmentforEnvironment,FoodandRuralAffairs,2010)areprimarilyused.DataonclimaticfactorswereobtainedfromtheNationalClimaticDataCenter(NCDC)(NationalOceanographicandAtmosphericAdministration,2010)andservedasinputfordifferentclimatechangescenarios.ThusclimatemodelsweredevelopedandprojectionsoffutureclimateweredonealongtheguidelinesandwithintheframeworksetbytheIPCCandUKCIP.Atool,ModelfortheAssessmentofGreenhousegasInducedClimateChange:AregionalClimateScenarioGenerator(MAGICC/SCENGEN),wasusedineffectingclimatechangescenarios(Wigley,2008).


Bycombiningpavementstructures,currentandprojectedclimaticagentsanddifferenttrafficlevelsinexperimentaldesigns,theperformanceofpavementsovertheirdesignliveswereanalyzedusingMEPDG.Thisinvolvedcomparingtheperformancedeteriorationsoftwoparalleldesigns,onewhichconsiderstheimpactsofclimatechangewithitsdifferentscenariosandonewhichdoesnotconsiderclimatechange.Thisisachievedbyusingasetofperformanceindicatorsforeachpavementtype.Ofparticularinterestishowpavementdistressesevolveunderuncertaintyinthedifferentemissionandclimatechangemodels.Totailordistressestomeetlocalpavementconditions,sensitivityanalysisisconductedtolocallycalibratedistresses.Subsequentanalysisintheresearchisbasedonresultsobtainedfromtheparallelcomparisonsbetweenpotentialclimatechangeandnochangestoclimate.ThemethodologyisillustratedintheflowchartinFigure1.2.ReportOutlineTosupporttheoverarchinggoalofinvestigatingthepotentialimpactsofclimatechangeonroadpavementsanditsunderlyinguncertainty,chapterswithinthereportarearrangedsoreaderscanappreciatetheextenttowhichthisphenomenoncanaffectpavementdesignandultimatelyperformance.Thischapterprovidesanoverviewoftheproblem,includingareviewofpaststudies,studyobjectivesandanoverviewofthemethodology.Chapter2investigateshowenvironmentaleffectspertainingtoclimatearecapturedinMEPDG.Itspecificallylooksathowthevariousclimaticfactorsareincorporatedinthedesignprocessandhowtheseaffecttheoverallperformanceofeachpavementtype.ThescienceofclimatechangeispresentedinChapter3andtheknowledgeestablishedsofarbyleadingresearchinstitutionsistabulated.MAGICC/SCENGENisalsointroducedinthischapter.Additionally,theprocessbywhichitcanbeusedtoexploreuncertaintiesrelatedtopotentialclimatechangeisdemonstrated.Chapter4looksathowclimaticfactorsandtheirrelateduncertainty,asdiscussedinChapter3,areemployedintheMEPDGsoftware.ThechapteralsoshowshowpavementperformanceisachievedinMEPDGusingdistresspredictionmodelsandhowthesecanbecalibratedtosuitlocalconditionsinwhichthedifferentpavementtypescanbefound.AcasestudyisusedinChapter5toillustratetheprocessbywhichthevariousstagesoftheresearchareputtogethertodetermineindepththeimplicationsofclimatechangeonpavementdesign.ConclusionsandrecommendationsarepresentedinChapter6.Appendicesdocumentmodelinputsandcomprehensiveresults.


Figure1.2Flowchartrepresentingthemethodology

Y

Emissionmodel AnalysisyearVariabilitylevel

MAGICCGlobalmean

temperatureandsealeveloutputs

Generalcirculationmodels(GCMs)

SCENGEN

Regionalclimatechangeoutputs

Selecttestsite

MEPDGdesigninputsOtherinputs:traffic,materials,structures

Climaticinputs

Historicaldata:FromMEPDG

Afterclimatechangescenarios

MEPDGanalysisandperformance

predictions

MEPDGanalysisandperformance

predictions

Comparisonanalysisatvariousvariabilitylevels

Finalcalibrationcoefficientstoadaptclimatechangein

pavementdesign

Adjustcoefficients

Sensitivityanalysisofthecoefficients

Significantdifferenceinprediction?

N


2. EnvironmentalEffectsintheMechanisticEmpiricalPavementDesignGuide(MEPDG)

IntroductionApavementmustbeabletofunctionandperformeffectivelywithintheenvironmentinwhichitisbuilt.Theenvironmentvariesacrosstheglobeatanyonetimeanditcanalsovarygreatlyacrosstimeatanyoneplace.Environmentalvariationscanhaveasignificantimpactonpavementmaterialsandtheunderlyingsubgrade,whichinturncandrasticallyaffectpavementperformance.Certainlyeveryenvironmentalconstituent(e.g.,solarflux,heat,wind,humidity,etc.)canhaveanincrementaleffectonpavement.However,thereareseveralconstituentsthatexertanoverridinginfluence.Thesevariablesaretemperature,precipitation,andfreeze/thawcycles.Eachvariableisbrieflydescribedintermsofthedamagecaused.TemperatureTemperaturevariationscancauseseverepavementdamageduetoexpansion,contractionand(inthecaseofrigidpavements)slabcurling.Smallamountsofexpansionandcontractionaretypicallyaccommodatedwithoutexcessivedamage,howeverextremetemperaturevariationscanleadtocatastrophicfailures.Flexibleandrigidpavementscansufferlargetransversecracksasaresultofexcessivecontractionincoldweather.Theeffectoftemperatureonasphaltpavementsisdifferentfromthatofconcretepavements.Temperatureaffectstheresilientmodulusofasphaltlayers,whileitinducescurlingofconcreteslab.Inrigidpavements,duetodifferencesintemperaturebetweenthetopandbottomofslab,temperaturestressesorfrictionalstressesaredeveloped.Whileinflexiblepavement,dynamicmodulusofasphalticconcretevarieswithtemperature.Rigidpavementsarealsopronetoslabbucklingasaresultofexcessiveexpansioninhotweatherandflexiblepavementpronetoruttingduetochannelizedtrafficandhightemperature.PrecipitationThequantityandintensityofprecipitation,intheformofrainandsnow,affectsthequantityofsurfacewaterinfiltratingintothesubgradeandthedepthofgroundwatertable.Poordrainagemayreduceshearstrength,orcausepumpingorlossofsupport.Moisture(intheformofaccumulatedwaterorrainfall)affectspavementsinseveralphasesofthepavementlifecycle:

Design.Certaintypesofsoilscanbehighlyexpansivewhenwet.Structuraldesignmustaccountforthisexpansiveness.

Construction.o Subgradeshouldbecompactedatoptimalmoisturecontent.Excessive

rainfallcanraisesubgrademoisturecontentwellbeyondthisvalueandmakeitvirtuallyimpossibletocompact.

o Hotmixasphalt(HMA)andPortlandcementconcrete(PCC)shouldnot


beplacedinwetconditions. DrivingConditions.Rainfallreducesskidresistanceandcancausehydroplaning

inseverelyruttedareasorotherareaswherewaterpondsontheroadsurface.Freeze/ThawFrostactionisacriticalpavementstructuraldesignconcerninpartsofthecountrythatregularlyexperiencegroundfreezing.Therearetwobasictypesoffrostactionwithwhichtocontend:

Frostheave:Anupwardmovementofthesubgraderesultingfromtheexpansionofaccumulatedsoilmoistureasitfreezes.Frostheavingofsoiliscausedbycrystallizationoficewithinthelargersoilvoidsandusuallyasubsequentextensiontoformcontinuousicelenses,layers,veins,orothericemasses.Anicelensgrowsthroughcapillaryriseandthickensinthedirectionofheattransferuntilthewatersupplyisdepletedoruntilfreezingconditionsattheinterfacenolongersupportfurthercrystallization.Astheicelensgrows,theoverlyingsoilandpavementwillheaveup,potentiallyresultinginacracked,roughpavement.Thisproblemoccursprimarilyinsoilscontainingfineparticles(oftentermedfrostsusceptiblesoils),whilecleansandsandgravels(smallamountsoffineparticles)arenonfrostsusceptible(NFS).Thethreeelementsnecessaryforicelensesandthusfrostheaveare: Frostsusceptiblesoil(significantamountoffines). Subfreezingtemperatures(freezingtemperaturesmustpenetratethesoil

and,ingeneral,thethicknessofanicelenswillbethickerwithslowerratesoffreezing).

Water(mustbepresent,eitherfromthegroundwatertable,infiltration,anaquifer,orheldwithinthevoidsoffinegrainedsoil).

Frostheavecausesdifferentialsettlementsandpavementroughness. Thawweakening:Aweakenedsubgradeconditionresultingfromsoilsaturation

asicewithinthesoilmelts.Thawingisessentiallythemeltingoficecontainedwithinthesubgrade.Astheicemeltsandturnstoliquiditcannotdrainoutofthesoilfastenoughandthusthesubgradebecomessubstantiallyweaker(lessstiff)andtendstolosebearingcapacity.Therefore,loadingthatwouldnotnormallydamageagivenpavementmaybequitedetrimentalduringthawperiods(e.g.,springthaw).

ClimaticInputsinMEPDGChangingtemperatureandmoistureprofilesinthepavementstructureandsubgradeoverthedesignlifeofapavementareconsideredinMEPDGthroughtheEnhancedIntegratedClimaticModel(EICM).TheEICMisaonedimensionalcoupledheatandmoistureflowprogramthat


simulateschangesinthebehaviorandcharacteristicsofpavementandsubgradematerialsinconjunctionwithclimaticconditionsoverseveralyearsofoperation.ItisfullylinkedtotheMEPDGsoftwareandinternallyperformsallthenecessarycomputations.TheuserinputstotheEICMareenteredthroughinterfacesprovidedaspartoftheMEPDGsoftware.TheEICMprocessestheseinputsandfeedsitsoutputstothethreemajorcomponentsoftheMEPDGframeworkmaterials,structuralresponses,andperformanceprediction.Thefollowinginformationthroughouttheentirepavement/subgradeprofilearepredicted:temperature,resilientmodulusadjustmentfactors,porewaterpressure,watercontent,frostandthawdepths,frostheave,anddrainageperformance(AppliedResearchAssociatesInc,2004a).Theinputsrequiredbytheclimaticmodelfallunderthefollowingbroadcategories:

Generalinformation Weatherrelatedinformation Groundwaterrelatedinformation Drainageandsurfaceproperties Pavementstructureandmaterials

TheuseofthenewThornthwaiteMoistureIndex(TMI)modelintheMEPDGsoftwaremakestheentryofdrainagepathandinfiltrationunnecessary.Thepavementstructureandmaterialsrelateddataareoutofthescopeandexcludedfromthisstudy.GeneralInformationThegeneralinformation,suchaspavementstructure,constructiondates,trafficopeningtime,isrequiredtoinitializethemoisturemodelintheEICM.Underthiscategory,thefollowinginputsspecificallyrelatetotheclimaticmodel:

Base/SubgradeConstructionCompletionMonthandYear. ExistingPavementConstructionMonthandYear. PavementConstructionMonthandYear TrafficOpeningMonthandYear

WeatherRelatedDataInputToaccomplishtheclimaticanalysisrequiredforincrementaldamageaccumulation,MEPDGrequiresfiveweatherrelatedparametersonanhourlybasisovertheentiredesignlifeforthedesignproject(21):

Hourlyairtemperature Hourlyprecipitation Hourlywindspeed Hourlypercentagesunshine(usedtodefinecloudcover)


Hourlyrelativehumidity

InMEPDG,theweatherrelatedinformationisprimarilyobtainedfromweatherstationslocatedneartheprojectsite.TheMEPDGsoftwareprovidesover800weatherstationscontaininghourlydataacrosstheUnitedStatesfromtheNationalClimaticDataCenter(NCDC)database.AllthedatasetsforeachstationaresavedinafilewithHCDextensionandcanbedownloadedfromthewebsiteforNCHRP137Aproject(http://www.trb.org/mepdg)(TRB,2011).IntheMEPDGreport,itstatesthatseveralofthemajorweatherstationshaveapproximately60to66monthsofclimaticdataateachtimestep(1hour)neededbytheEICM.Otherweatherstationscouldhavelessthanthisamountofdata,however,theDesignGuidesoftwarerequiresatleast24monthsofactualweatherstationdataforcomputationalpurposes(AppliedResearchAssociatesInc,2004a).Theclimaticdatabasecanbetappedintobysimplyspecifyingthelatitude,longitude,andelevationoftheprojectsiteinMEPDGsoftware.Oncetheglobalpositioningsystem(GPS)coordinatesandelevationarespecifiedforthedesignprojectsite,theMEPDGsoftwarehighlightsthesixclosestweatherstationstothesitefromwhichtheusermayselectanynumberofstationstogenerateavirtualprojectweatherstation.Afterselectingtheclimatestationsandinputtingthewatertabledepthforthedesign,clickgeneratebuttonandalltheclimaticdatasetsrequiredaresavedinafilewithanicmextensionthroughtheEICMnumericalengine.TheclimategeneratingscreenwindowisshowninFigure2.1.

Figure2.1ClimaticGeneratingWindowinMEPDG


Intheclimatedatagenerationprocess,therearethreetypesoffilesthatareusedbytheEICMnumericalengineintheMEPDGsoftware:icmfile,hcdfile,andstation.datfileAsshownabove,icmfilesaregeneratedfromhcdfilesandstation.datfile.Eachfilehasitsuniquefileformat,whichisdocumentedinAppendixA.GroundwaterTableDepthInputThegroundwatertabledepth,intendedtobeeitherthebestestimateoftheannualaveragedepthortheseasonalaveragedepth,isanotherimportantparameterneededtobeinputtotheMEPDGsoftware.AtinputLevel1,itcouldbedeterminedfromprofilecharacterizationboringspriortodesign.AtinputLevel3,anestimateoftheannualaveragevalueortheseasonalaveragescanbeprovided,suchasusingthedataproducedbytheUnitedStatesGeologicalSurvey(USGS).MajorOutputsoftheEICMTheoutputoftheEICMcanbedescribedontwofrontsinternalandexternal.BothformsofoutputsoftheEICMaretransparenttotheuserwiththedifferencebeingthattheinternaloutputsarenotpassedontoothercomponentsoftheDesignGuidesoftware(e.g.,structuralresponsecalculationmoduleortheperformancepredictionmodule),whiletheexternaloutputsare.However,theuserhasfullcontrolovertheinputsthatdriveboththeseoutputs(e.g.,watertabledepths,climaticinformationfortheprojectsite).RegardingtheinternaloutputoftheEICM,thecomputationalengineoftheEICMdeterminesvaluesofvolumetricwatercontent,w,andtemperatureateachnodeovertimebasedonabovementionedclimaticinput.Thevaluesofw aredividedbythesaturatedvolumetricwatercontents,sat,togetvaluesofdegreeofsaturation,S.WithnooscillationsintheinputgroundwatertableandnocracksintheAClayer,valuesofS areessentiallyvaluesatastateofequilibrium,Sequil,unlessfreezingorthawrecoveryisinprogress.ValuesofSequil,togetherwithvaluesofdegreeofsaturationatoptimumconditions,Sopt,arethenusedtocomputetheunboundlayermodulusadjustmentfactorforunfrozenconditions,FU,ateachnode.Theoutputtemperaturesareusedtosignalfreezingatanodeandanadjustmentfactorforfrozencondition,FF,iscomputedateachfreezingnode.Thawingnormallyfollowsfreezing,assignaledbytheriseintemperatureabovethefreezingpoint.Duringtherecoveryperiod,materialtype/propertiesareusedtocomputetherecoveryratio,RR,atrecoveringnodes.TheseRR values,togetherwithreductionfactorsduetothawing,RF,areusedtocomputeandadjustmentfactorforrecoveringconditions,FR,ateachrecoveringnode.TheexternalEICMoutputsfeeddirectlyintothematerialscharacterization,structuralresponsecomputation,andperformancepredictionmodulesoftheMEPDGsoftware,includingthefollowing:

UnboundmaterialMR adjustmentfactorasfunctionofpositionandtimevaluesofcompositeenvironmentaleffectsadjustmentfactor,Fenv,arecomputedforeverysublayerfromthevaluesofFF, FR,orFU ateachnode.ThesublayeringisinternallydefinedbytheEICMandisafunctionofthefrostpenetrationdepth,


amongotherfactors.TheseFenv factorsaresentforwardtostructuralanalysismodulesoftheMEPDGsoftware.

Temperaturesatthesurfaceandatthemidpointofeachasphaltboundsublayerthesevaluesaresubjectedtostatisticalcharacterizationforeveryanalysisperiod.Themean,standarddeviation,andquintilepointsaresentforwardforuseinthefatigueandpermanentdeformationpredictionmodels.

Valuesofhourlytemperatureatthesurfaceandatasetdepthincrement(everyinch)withintheboundlayersforuseinthethermalcrackingmodel.

Volumetricmoisturecontentanaveragevalueforeachsublayerisreportedforuseinthepermanentdeformationmodelfortheunboundmaterials.

TemperatureprofileinthePCChourlyvaluesaregeneratedforuseinthecrackingandfaultingmodelsforJPCPandCRCPpavements.

NumberoffreezethawcyclesandfreezingindexarecomputedforuseinJPCPperformanceprediction.

RelativehumidityvaluesforeachmontharegeneratedforuseintheJPCPandCRCPmodelingofmoisturegradientsthroughtheslab.


3. ClimateChangeandVariabilityIntroductionTheworldsleadingclimatescientistshavereachedconsensusthathumanactivityintheformofgreenhousegas(GHG)emissionsiswarmingtheplanetinwaysthatwillhaveprofoundandunsettlingimpactsonnaturalresources,energyuse,ecosystems,economicactivity,andpotentiallyqualityoflife.Manystudieshavealreadyexaminedthepotentialimpactsofclimatechangeonbroadsectorsoftheeconomy,suchasagricultureandforestry,butfewhavestudiedtheimpactsontransportation(TransportationResearchBoard,2008,Walther,2002,Kheshgiletal,2000).Transportationinfrastructuresystemsaredesignedfortypicalweatherpatterns,takingintoconsiderationlocalclimateandmakingprojectionsbasedonitshistorywithinthelocality.Shouldanyprofoundfutureclimatechangeoccur,transportationwillbeprimarilyaffectedthroughincreasesinseveraltypesofweatherandclimateextremes,suchasveryhotdays;intenseprecipitationevents;intensehurricanes;drought;andrisingsealevels,coupledwithstormsurgesandlandsubsidence(TransportationResearchBoard,2008).Theimpactswillvarybytransportationmodeandregionofthecountry,buttheywillbewidespreadandcostlyinbothhumanandeconomictermsandwillrequiresignificantchangesineveryfacetoftheprovisionoftransportationinfrastructure.IPCCSpecialReportEmissionsScenariosGreenhousegasemissionsfromanthropogenicsourceshavebeenassociatedwithchangingglobalclimatictrendsandhavebeenincreasingsteadilyoverthepastfewdecades(10).EstimatesoffutureGHGemissionlevelsbeginwithidentifyingarangeofpossiblefuturescenariosthatrelatetosuchfeaturesaspopulationandeconomicgrowth,andtypeofpowergeneration.ThescenariosusedinthisresearchwereadoptedfromtheIPCCSpecialReportonEmissionsScenarios(SRES)(IPCC,2011).TherearesixSRESscenariosbeingwidelyusedbasedonfourfamilies:

TheA1scenariofamilydescribesafutureworldofveryrapideconomicgrowth,globalpopulationthatpeaksinmidcenturyanddeclinesthereafter,andtherapidintroductionofnewandmoreefficienttechnologies.TheA1scenariofamilydevelopsintothreegroupsthatdescribealternativedirectionsoftechnologicalchangeintheenergysystem:fossilintensive(A1FI),nonfossilenergysources(A1T),orabalanceacrossallsources(A1B).

TheA2scenariofamilydescribesaveryheterogeneousworld.Theunderlyingthemeisselfrelianceandpreservationoflocalidentities.Economicdevelopmentisprimarilyregionallyorientedandpercapitaeconomicgrowthandtechnologicalchangearemorefragmentedandslowerthaninotherscenarios.

TheB1scenariofamilydescribesaconvergentworldwiththesameglobalpopulationthatpeaksinmidcenturyanddeclinesthereafter,asintheA1storyline,


butwithrapidchangesineconomicstructurestowardaserviceandinformationeconomy,withreductionsinmaterialintensity,andtheintroductionofcleanandresourceefficienttechnologies.Theemphasisisonglobalsolutionstoeconomic,social,andenvironmentalsustainability.

TheB2scenariofamilydescribesaworldinwhichtheemphasisisonlocalsolutionstoeconomic,social,andenvironmentalsustainability.ItisaworldwithcontinuouslyincreasingglobalpopulationataratelowerthanA2,intermediatelevelsofeconomicdevelopment,andlessrapidandmorediversetechnologicalchangethanintheB1andA1scenarios.

ClimateChangeVariabilityThereisbroadconsensusthatanthropogenicwarmingisoccurring.However,theobviouslimitationstoperformingscientificexperimentsontheglobalclimatesystemanditsextremelycomplicatednaturerenderourunderstandingincomplete.The2007IPCCreportonthephysicalsciencebasisofclimatechangeincludesmanymodelswhichshowthewiderangeoftemperatureincreasepredictions(IPCC,2007b).Figure3.1givesasenseoftheuncertaintiesinvolvedinclimatechangemodelingforthe10models(Andronova,2001;Annan,2005;Forest,2002;Forest,2006;Forster,2006;Frame,2005;Gregory,2002;Hegerl,2006;Knutti,2002;Schneider,2006ascitedinIPCC,2007b).Eachmodelattemptstotakewhatweknowabouttheclimatesystemanddeterminetheprobabilitythattheclimatewillstabilizewithaglobalmeantemperatureincreasefrom010C.Whilethereisbroadagreementacrossthemodelsthattemperatureincreaseswilloccur,thedistributionsvaryconsiderably.

a)Probabilityofequilibriumtemperaturechange(climatesensitivity)indifferentclimatemodels.b)Confidenceinterval(5%95%)fortemperaturechangeCirclesrepresentthemediantemperatureandtrianglesthemaximumprobability.Figure3.1ProbabilitiesofEquilibriumTemperatureIncreasesinSampleofDifferentClimateModels(ascitedinIPCC,2007b)

TemperatureChange(oC) TemperatureChange(oC)


Asaresult,thereareamyriadofuncertaintiesindividualsconfrontwhenmakingdecisionsthataffect,orareaffectedbyclimatechange.Ingeneral,therearethreefundamentalsourcesofuncertaintytobeaddressed:

1. Greenhouseandothergasemissions:Variousemissionmodelshavebeendevelopedworldwidebutpredictionsvarysignificantly.Forexample,theIPCCSRESmodelsprojectaverywiderangeofemissionsofkeygreenhousegases(GHG);

2. Climatesensitivity:Climatesensitivityisameasureofhowresponsivethetemperatureoftheclimatesystemistochangeintheradiativeforcing.ItisusuallyexpressedasthetemperaturechangeassociatedwithadoublingoftheconcentrationofCO2intheearthsatmosphere.Howmuchglobalmeantemperature(GMT)willwarmforaCO2doublinghasnotbeenfullyunderstood;

3. Patternofregionalchange:Thisthirdsourceofuncertaintyconcernsrelativeregionalchanges.Someareaswillwarmmorethanothersandsomeareaswillreceiveincreasedprecipitationwhileothersfacedecreasesinprecipitation.

Quantifyinguncertaintyischallenging.Thereareaspectsofclimatechangeaboutwhichwearealmostcertain(thephysicalchemistry),andareasinwhichuncertaintyissignificant(e.g.theeffectofclouds,theocean,theresponseofbiologicalprocesses,climatechangemitigation).Asaresult,variousapproachesmaybeadoptedtocharacterizetheuncertainty.Thesimplestbutwidelyusedapproachistoassumetheclimaticparametersaresubjecttonormaldistributions.Forexample,foratemperaturerecordthatisstationary,thedistributionisassumedtobenormal(thebellcurve)andcharacterizedbytwostatisticalparameters,themeanandvariance.Iftheclimatechangeundergoesawarmingwithoutanychangeinthevariancethenthewholebellcurvemovessideways.Theconsequenceofashifttoahighermeanisthattherearefewercolddaysandmorehotdays,andahigherprobabilitythatpreviousrecordhightemperatureswillbeexceeded.Ifhowever,thereisanincreaseinvariancebutnochangeinthemeanthebellcurvebecomesfatterandlower.Theconsequenceisthattherearecoolerandhotterdaysandahighprobabilitythatpreviousrecordsforboththecoldestandhottestdayswillbebroken.Ifboththemeanandthevarianceincreasethenthebellcurveshiftssidewaysandbecomeslowerandfatter.Theeffectisforrelativelylittlechangeinthefrequencyofcoldweatherortheoccurrenceofextremelowtemperatures,butabigincreaseinhotweatherandpreviousrecordhightemperaturesbeingexceededfarmoreoften.ThethreecombinationsofthemeanchangingovertimeandthevariancearoundthemeanareshowninFigure3.2.


Figure3.2ClimateChangeUncertainties


MAGICC/SCENGENSoftwareMAGICCandSCENGENareasuiteofmodelsthatdeterminetheregionaldetailsoffutureclimaticchangeforspecifiedemissionsscenarios,togetherwithestimatesoftheiruncertainties(Wigley,2008).Itisacoupledgascycle/climatemodel(MAGICC;ModelfortheAssessmentofGreenhousegasInducedClimateChange)thatdrivesaspatialclimatechangeSCENarioGENerator(SCENGEN).AflowchartdescribinghowMAGICC/SCENGENisconfiguredasshowninFigure3.3.MAGICChasbeenoneoftheprimarymodelsusedbyIPCCsince1990toproduceprojectionsoffutureglobalmeantemperatureandsealevelrise.TheclimatemodelinMAGICCisanupwellingdiffusion,energybalancemodelthatproducesglobalandhemisphericmeantemperatureoutputtogetherwithresultsforoceanicthermalexpansion.TheMAGICCclimatemodeliscoupledinteractivelywitharangeofgascyclemodelsthatgiveprojectionsfortheconcentrationsofthekeygreenhousegases.Climatefeedbacksonthecarboncyclearethereforeaccountedfor.Theyears1990and2100arethedefaultstartandendoutputyearsusedbythesoftware,buttheycanbechangedbytheuser.ThemainaimsofMAGICCare:

Tocomparetheglobalmeantemperatureandsealevelimplicationsoftwodifferentemissionsscenarios.Forconvenience,MAGICCreferstotheseasa"Reference"scenarioanda"Policy"scenario.However,anytwoscenariosmaybecompared.

Todeterminethesensitivityofthetemperatureandsealevelresultsforanychosenemissionsscenariotochangesinanduncertaintiesinmodelparameters,suchastheclimatesensitivity.Basicuncertaintyrangesanda"bestestimate"resultarecalculatedbydefault.Inaddition,theusermayselectasetofmodelparametersthatdiffersfromthebestestimatesettoexamineuncertaintiesassociatedwithmodelparameteruncertaintiesinmoredetail.

GlobalmeantemperaturesfromMAGICCareusedtodriveSCENGEN.SCENGENusesaversionofthepatternscalingmethoddescribedinSanteretal.(1990)toproducespatialpatternsofchangefromadatabaseofatmosphere/oceanglobalclimatemodel(AOGCM).Thepatternscalingmethodisbasedontheseparationoftheglobalmeanandspatialpatterncomponentsoffutureclimatechange,andthefurtherseparationofthelatterintogreenhousegasandaerosolcomponents.Spaalpaernsinthedatabasearenormalizedandexpressedaschangesper10Cchangeinglobalmeantemperature.Thesenormalizedgreenhousegasandaerosolcomponentsareappropriatelyweighted,added,andscaleduptotheglobalmeantemperaturedefinedbyMAGICCforagivenyear,emissionsscenarioandsetofclimatemodelparameters.FortheSCENGENscalingcomponent,theusercanselectfromanumberofdifferentAOGCMsforthepatternsofgreenhousegasinducedclimate.Projectionsofabsolute(ratherthanrelative)futureclimateconditionsforanyfuturedatecoveredbytheinputemissionsdatacanbeobtainedaswell.Toproducetheseprojections,SCENGENaddstheclimatechangeinformationtoobservedbaselineclimatedata(198099means).Theseresultsaregivenasarrayfilesonastandard2.5x2.5degreelatitude/longitudegridanddisplayedasmaps.


Userchoicesintheproductionofsuchfutureclimateorclimatechangescenariosare:afuturedate;aclimatevariable(temperature,precipitationorMeanSeaLevelPressure(MSLP));eitheraspecificmonthorseasonortheannualmean;andoneormoreoftheAOGCMsinSCENGEN'slibraryofmodelresults.Climatechangefieldsareconstructedusingapatternscalingmethod.Beyondsimpleclimatechangescenarioconstruction(i.e.,changesinthemeanclimatestate),SCENGENproducesspatialpatternresultsfor:changesininterannualvariability;twodifferentformsofsignaltonoiseratio(toassessthesignificanceofchanges);probabilisticoutput(thedefaultbeingtheprobabilityofanincreaseinthechosenclimatevariable);andawiderangeofmodelvalidationstatisticsforindividualmodelsorcombinationsofmodelstoassistintheselectionofmodelsforscenariodevelopment.Ascanbeseen,thetoolMAGICC/SCENGENcanbeusedtoaddressthethreeuncertaintiesandallowsuserstoexplore:

GHGemissionscenarios,thusaddressinguncertainty#1; Climatemodeluncertainties,includingclimatesensitivity,aerosolfeedbacks,

carboncycle,thermohalinecirculation,andicemelt,thusaddressinguncertainty#2;

SCENGENusestheregionalpatternofrelativechangesacross20GeneralCirculationModels(GCMs)toaverageregionalGCMsoutputsbecauseitcontrolsfordifferencesinclimatesensitivityacrossmodels.Asaresult,thethirdvariabilityisaddressed.


Figure3.3StructureoftheMAGICC/SCENGENSoftware(Wigley,2008)


4. IncorporatingClimateChangeintotheMEPavementDesign

IntroductionMEPDGislargelybasedonmechanisticengineeringprinciplesthatprovideafundamentalbasisforthestructuraldesignofpavementstructures.Thedesignprocedureswerecalibratedusinghistoricalclimatedata(withoutconsideringthepotentialofclimatechange),designinputsandperformancedatalargelyfromthenationalLTPPdatabase.Whateverbiasincludedinthiscalibrationdataisnaturallyincorporatedintothedistresspredictionmodels.Becauseofthedifferencesbetweennationalconditionsandlocalconditionssuchasclimate,materialproperties,trafficpatterns,constructionandmanagementtechniques,thenationalcalibrationmaynotbeentirelyadequateforspecificregionsofthecountrythusamorelocalorregionalcalibrationandvalidationareneededforlocalconditions.Inaddition,thedistressmechanismsarefarmorecomplexthancanbepracticallymodeled;therefore,theuseofempiricalfactorsandcalibrationisnecessarytoobtainrealisticperformancepredictions. PavementPerformancePredictioninMEPDGPavementperformanceisprimarilyconcernedwithfunctionalandstructuralperformance.Thestructuralperformanceofapavementrelatestoitsphysicalcondition(suchasfatiguecrackingandruttingforflexiblepavements,andjointfaultingandslabcrackingforrigidjointedpavements).Severalofthesekeydistresstypescanbepredicteddirectlyusingmechanisticconceptsandareconsideredinthedesignprocess.Ridequalityisthedominantcharacteristicoffunctionalperformance,asmeasuredbytheInternationalRoughnessIndex(IRI).InMEPDG,IRIisestimatedincrementallyovertheentiredesignperiodbyincorporatingdistressessuchascracking,rutting,faulting,andpunchoutsasmajorfactorsinfluencingthelossofsmoothnessofapavement.ThegeneralhypothesisofsmoothnessmodelsisthatthevariousdistressesresultinginsignificantchangesinsmoothnessarerepresentedbyseparatecomponentswithintheMEPDGmodels,asshowninEquation4.1(AppliedResearchAssociatesInc,2004b).

0 1 ( )1 ( )( )= ( )D t n D t n j j j jS t S a S a S b S c M (Eqn.4.1)WhereS(t)denotespavementsmoothnessataspecifictimet;S0initialsmoothnessimmediatelyafterconstruction;SD(t)(i=1ton)changeofsmoothnessduetotheithdistressatagiventimetintheanalysisperiod;a(i=1,,n),bj,cjareregressioncoefficients;Sjchangeinsmoothnessduetositefactors(subgradeandage);Mjchangeinsmoothnessduetomaintenanceactivities.Thefollowingsectionexaminesthedifferentperformancemodelsasusedinthisresearchindetail.


FlexiblePavementPerformanceModelsPerformancemodelsforflexiblepavementswereusedinanalyzingthefollowingdistresses:rutting,bottomupcrackingandroughness.InMEPDG,ruttingisdefinedasaloadassociateddistressinflexiblepavementsystemsnormallyappearingaslongitudinaldepressionsinwheelpathsaccompaniedbysmallupheavalstothesides(AppliedResearchAssociatesInc,2004c).Thewidthanddepthofaruttingprofileishighlydependentonthepavementstructure(layerthicknessandquality),trafficmatrixandquantityandtheenvironmentalconditionsatthedesignsite.Ruttingresultsfromdensificationandpermanentdeformationunderloadscombinedwithdisplacementofpavementmaterials(Millsetal,2007).Pavementsafflictedbyruttingposeassafetyconcernsbymodifyingdrainagecharacteristicsoftheroadway,therebycontributingtovehicleaquaplaningandreducingskidresistance.Ruttingalsoreducesridingqualityoftheroadway.Ruttingcanoccurinalllayersofapavementsystemanddesignersmodeltotalpermanentdeformationasaproductofcumulativerutsinalllayers.ForMEPDG,apredictiveruttingsystemwasdevelopedtoevaluatepermanentdeformationinallrutsusceptiblelayerswithinthepavementstructure.Layersgenerallyanalyzedforruttingaretheasphalticlayerandallunboundmateriallayers.Consideringthedifferentlayers,thefieldcalibratedruttingmodelusedintheDesignGuideforasphalticmixturesisgivenas: 10

.T.N. (Eqn.4.2)Where,,=Calibrationfactorsfortheasphaltmixturesrutmodel.=Accumulatedpermanentstrain.=Resilientstrain.T=Mixtemperature(degF).N=Numberofloadrepetitions.ThebasicrelationshipusedforcharacterizingpermanentdeformationinunboundlayersasstatedintheDesignGuideisgivenas:N e

h Eqn.4.3

Where=Permanentdeformationforthelayer/sublayer.N=Numberoftrafficrepetitions.,,=Materialproperties.=Resilientstrainimposedinlaboratorytesttoobtainmaterialproperties,,,.=Averageverticalresilientstraininthelayer/sublayerasobtainedfromtheprimaryresponsemodel.h=Thicknessoflayer/sublayer.=Calibrationfactorfortheunboundgranularandsubgradematerials.Individualandcumulativerutdepthsarefoundasafunctionoftimeandtrafficrepetitions.Damageinducedbyruttingisestimatedforeachsubseasonatthemiddepthofeachsublayerwithinthepavementandtheplasticstrainaccumulatediscomputedattheendofeachsubseason.TheoverallpermanentdeformationattheendoftheseasonisgivenbyPD h Eqn.4.4


WherePD=pavementpermanentdeformation.nsublayers=numberofsublayers. =Totalplasticstraininsublayeri.h=Thicknessofsublayeri.Theprocessisrepeatedforeachloadlevel,monthandsubseasonoftheanalysisperiod.Fatiguecracksareaseriesofinterconnectedcrackscausedbyfatiguefailureoftheasphalticsurface(orstabilizedbase)byrepeatedloading(32).Theactionofrepeatedortrafficloadsinducestensileandshearstressesinlayersandcausefatiguecrackstoinitiateatpointswherethesecriticalstrainsandstressesoccur.Themostimportantfactorsinthelocationofcriticalstrainsorstressesarethelayerstiffnessandtheloadconfiguration(AppliedResearchAssociatesInc.,2004d).Themorecommonformoffatiguecrackinginitiatesatthebottomoftheasphalticlayerandpropagatesuptothesurface.Thisphenomenonisknownasbottomupcracking.Amorerecentformoffatiguecracking,topdowncracking,whichstartsfromthesurfaceandpropagatesdownwards,hasalsobeenobservedandisundergoingfurtherresearch.Assuch,onlybottomupcrackingisanalyzedinthisstudy.Fatiguecrackingleadstoalossinthestructuralintegrityoftheflexiblepavementandreducesitoverallserviceability.Cracksallowwater,typicallyrunoff,toseepintothepavementstructureandweakenunderlyinglayers.Fatiguecrackscanalsocontributetotheformationofotherdistressessuchasroughness.ThemostcommonlyusedfatiguemodelsarethosedevelopedbyShellOil(Bonnaureetal,1980)andtheAsphaltInstitute(AsphaltInstitute,1982).Theoverallgeneralformofthesetwomodelsisgovernedbyamathematicalrelationshipgivenas:N Ck

Eqn.4.5

WhereN=Numberofrepetitionstofatiguecracking.=Tensilestrainatthecriticallocation.E=Stiffnessofthematerial.k, k, k=Laboratoryregressioncoefficients.C=LaboratorytofieldadjustmentfactorThedifferencesbetweenthetwomodelslieinthelaboratoryregressioncoefficientsandthelaboratorytofieldadjustmentfactor.InMEPDG,fatiguecrackingpredictionwasachievedbyfocusingonthesetwomodels.ThemodifiedmodelusedintheDesignGuidetocalibratefatiguecrackingtoactualfieldperformanceisrepresentedbytherelationship:N 0.00432 C k

Eqn.4.6

C 10 Eqn.4.7M 4.84 0.69 Eqn.4.8WhereV=effectivebindercontent(%).V=airvoids(%).,,=Calibrationparameters.InMEPDG,thechosenfunctionalperformanceindicatorispavementsmoothnessasindicatedbytheInternationalRoughnessIndex(IRI)(AppliedResearchAssociatesInc.,2004).TheAmericanSocietyofTestingandMaterialsdefinesroughnessasthedeviationfromatrueplanarsurfacewithcharacteristicdimensionsthataffectsvehicledynamics,ridequality,


dynamicloads,anddrainage(AmericanSocietyofTestingMaterials,2006).Roadroughnesshasanappreciableimpactonvehicleoperatingcostsandonthesafety,comfort,andspeedoftravel.Italsoincreasesthedynamicloadingimposedbyvehiclesonthesurface,acceleratingthedeteriorationofthepavementstructure.Roughnesscanalsohaveadverseeffectsondrainage,causingwatertopondonthesurface,withsubsequentimpactsonboththeperformanceofthepavementandvehiclesafety(Salehetal,2000).InternationalRoughnessIndex(IRI)isthewidelyacceptedstandardformeasuringroadroughness.ResearchhasshownIRIissignificantlyaffectedbydistressessuchasrutting,fatiguecracking,potholes,depressionsandswellingscausedbysoilmovements.OtherfactorsthataffectIRIaredesign,siteandclimaticparametersaswellastheinitialasconstructedIRIofthepavement(AppliedResearchAssociatesInc,2004b).TheapproachutilizedintheDesignGuideforpredictingroughnesswastopredictitovertimeasafunctionoftheinitialIRIandkeydistresstypes.ThebasicdesignpremisefortheDesignGuidewasthatincrementalincreasesinsurfacedistresscauseincrementalincreasesinsurfaceroughness.Usingbasetype,threeequationsweredevelopedfornewflexiblepavementsandtheseareshownbelow:ForConventionalFlexiblePavementwithThickGranularBase:IRI IRI 0.0463 SF e

1 0.00119TC 0.1834COV 0.00384FC

0.00736BC 0.00155LC Eqn.4.9WhereIRI=IRImeasuredwithinsixmonthsafterconstruction,m/km.TC=Totallengthoftransversecracks(low,medium,andhighseveritylevels),m/km.COV=Rutdepthcoefficientofvariation,percent.FC=Totalareaoffatiguecracking(low,medium,andhighseveritylevels),percentofwheelpatharea,%.BC=Totalareaofblockcracking(low,medium,andhighseveritylevels),percentoftotallanearea,%.LC=Mediumandhighseveritysealedlongitudinalcracksoutsidethewheelpath,m/km.Age=Ageafterconstruction,years.SF .

. Eqn.4.10

WhereR=Standarddeviationinthemonthlyrainfall,mm.R=Averageannualrainfall,mm.P.=Percentpassingthe0.075mmsieve.P.=Percentpassingthee0.02mmsieve.PI=Plasticityindex.FI=Averageannualfreezingindex.ForFlexiblePavementwithAsphaltTreatedBase:IRI IRI 0.0099947Age 0.0005183FI 0.00235FC 18.36 0.9694P Eqn.4.11


WhereTC=Averagespacingofhighseveritytransversecracks,m.P=Areaofhighseveritypatches,percentoftotallanearea,%.FI=Averageannualfreezingindex.Age=Ageafterconstruction,years.ForFlexiblePavementwithCementTreatedBase:IRI IRI 0.00732FC 0.07647SD 0.0001449TC 0.00842BC 0.0002115LC Eqn.4.12WhereLC=Mediumandhighseveritysealedlongitudinalcracksoutsidethewheelpath,m/km.SD=Standarddeviationoftherutdepth,mm.PavementPerformanceModelsforJPCPPerformanceofjointedplainconcretepavements(JPCP)underdifferentclimatechangescenarioswasanalyzedusingthefollowingdistressesasbenchmarks:faulting,andtransversecracking.Jointfaultingisthedifferenceinelevationbetweenadjacentjointsatatransversejoint(AppliedResearchAssociatesInc,2004e).Faultingisusuallycausedbypumping,whichissimplythemovementoferodiblematerialbywaterpressurewithinthepavementstructureundertheactionofheavyaxleloadsorinadequateloadtransferatthejoints.Thisformsabuildupofmaterialbeneaththeapproachcornerofaslab,whilstformingavoidundertheleadcorneroftheadjacentslab,therebycreatingdifferentialelevationbetweenthetwoslabs.Faultingcanalsobecausedbyslabsettlement,curlingandwarping;andisacontributingfactorofroughnessinrigidpavements(WSDOT,2011).Informulatingamechanisticempiricalmodelforfaulting,theDesignGuideexaminedfourmaincomponents:damageduetoaxleloadapplications,inadequateloadtransfer,erodibilityofunderlyingmaterialsandthepresenceoffreewater.TheGuidethenusedincrementaldamageaccumulationasitsapproachindevelopingthefaultingmodel,whereincrementsareobservedmonthly.Thefaultingateachmonthisdeterminedasasumoffaultingincrementsfromallpreviousmonthsinthepavementlifesincetrafficopeningusingthismodel:Fault Fault Eqn.4.13Fault C FAULTMAX Fault DE Eqn.4.14FAULTMAX FAULTMAX C DE Log1 C 5 Eqn.4.15FAULTMAX C Log1 C 5 Log

Eqn.4.16WhereFault=Meanjointfaultingattheendofmonthm,in.Fault=Incrementalchange(monthly)inmeantransversejointfaultingduringmonthi,in.FAULTMAX Maximummeantransversejointfaultingformonthi,in.FAULTMAX Initialmaximummeantransversejointfaulting,in.EROD=Base/subbaseerodibilityfactor.DE Differentialdeformationenergyaccumulatedduringmonthi. Maximummeanmonthlyslabcornerupward


deflectionPCCduetotemperaturecurlingandmoisturewarping.P=Overburdenonsubgrade,lb.P=Percentsubgradepassing#200sieve.WetDays=Averageannualnumberofwetdays(greaterthan0.1inrainfall).C C C FR. Eqn.4.17C C C FR. Eqn.4.18WhereFR=Basefreezingindexdefinedaspercentageoftimethetopbasetemperatureisbelowfreezing(32temp.CthroughCarecalibrationconstantsTransversecracking,aprimarystructuralfatiguedistresstypeofJPCP,ischaracterizedbyitsinitiationfromonelongitudinaledgeofaconcreteslabfollowedbyadiagonalprogressionacrosstheslabtotheotherlongitudinaljointoratransversejoint(39).Theyareusuallycausedbyacombinationofheavyloadrepetitionsandstressesduetotemperaturegradient,moisturegradientanddryingshrinkage(Huang,2004).Anothercausecouldbeasaresultofpoorconstruction(PapagiannakisandMasad,2008).FortheDesignGuide,themechanisticempiricalpredictionfortransversecrackingincludesaniterativedamageaccumulationalgorithmwheredamageisaccumulatedonamonthlybasisovertheanalysisperiod.Thealgorithmconsideredtruckaxleloadings,thermalgradientsandmoisturegradientsinthedevelopmentofthepredictionmodel.Assuchtrafficinformation,climaticfactors,designfeaturesandinformationonmaterialsusedindifferentlayerswithintheJPCPstructureserveasusefulsourcesofinformationfortransversecrackprediction.TheincrementaldamagealgorithmusedintheDesignGuideispresentedasfollows:FD ,,,,,,,,,, Eqn.4.19WhereFD=totalfatiguedamage.n,,,=appliednumberofloadapplicationsatconditioni, j, k, l, m, n.N,,,=allowablenumberofloadapplicationsatconditioni, j, k, l, m, n.i=age(accountsforchangeinPCCmodulusrapture,layerbondcondition,deteriorationofshoulderLoadTransferEfficiency).j=month(accountsforchangeinbaseandeffectivedynamicmodulusofsubgradereaction).k=axletype.l=loadlevel(incrementalloadforeachaxletype).m=temperaturedifference.n=trafficpath.Theappliednumberofloadapplicationsn,,,,,istheactualnumberofaxletypekofloadlevellthatpassedthroughtrafficpathnundereachcondition(age,seasonandtemperaturedifference).Theallowablenumberofloadapplicationsisdeterminedusingthefollowingfieldcalibratedfatiguemodel:logN,,,,, C ,,,,,

0.4371 Eqn.4.20WhereN,,,=allowablenumberofloadapplicationsatconditioni, j, k, l, m, n.MR=PCCmodulusofraptureatagei,psi.,,,=appliedstressatconditioni, j, k, l, m, n.C, C=calibrationconstants.


AnalysisofroughnessforJPCPfollowedthatforflexiblepavements.Noonefundamentalmechanismcouldbeidentifiedasthecause,butseveralfactorscametoplaywhenconsideringroughnessasadistress.Thesefactorsincludeotherstructuralandnonstructuraldistressessuchasfaulting,cornerbreaks,longitudinalandtransversecracking;surfacedefectssuchasinitialsmoothness;maintenanceregimens;andothervariableslikeage.Combiningallthesefactorsandvariables,theequationforpredictingJPCProughnessintheDesignGuideisgivenas:IRI IRI 0.013 TC 0.007 SPALL 0.005 PATCH 0.0015 TFAUL 0.45 SF Eqn.4.21WhereTC=percentageofslabswithtransversecracking(allseverities).SPALL=percentageofjointswithspalling(allseverities).PATCH=pavementsurfaceareawithflexibleandrigidpatching(allseverities),percent.TFAULT=totaljointfaultingcumulatedperkm,mm.SF=sitefactor=Age 1 FI 1 P/1000000,,inwhichAge=pavementageinyears,FI=freezingindex,0Cdays,P=percentsubgradematerialpassingthe0.075mmsieve.PavementPerformanceModelsforCRCPTwodistresses:roughnessandpunchoutswereusedasindicatorstomonitortheeffectofpotentialclimatechangeoncontinuouslyreinforcedconcretepavements(CRCP).RoughnessforCRCPfollowedthesamedescriptiongiveninthesectionsforflexibleandJPCP.Aswasthecasefortheaforementionedpavementtypes,roughnessinCRCPisalsotriggeredbyanumberoffactorssuchasage,initialroughnessafterconstructionanddistressesformedasaresultofinteractionsbetweentraffic,siteandenvironmentalfactors.FollowingJPCP,factorsthatinfluenceroughnesscanbeclassifiedasstructural,surfacedefectsandmaintenancerelated.Examplesofstructuralfactorsarepunchouts,transversecracksandpumping.SurfacedefectsincludeinitialIRI,scalingandmapcracking.Amaintenancerelatedfactorispatching.ThemodelforpredictingroughnessforCRCPasusedintheDesignGuideisgivenas:IRI IRI 0.003 TC 0.008 PUNCH 0.45 SF 0.2 PATCH Eqn.4.22WhereTC=numberofmediumandhightransversecracks/km.PUNCH=numberofmediumandhighseveritypunchouts/km.PATCH=percentagepavementsurfacewithpatching(MHseverityflexibleandrigid).SF=sitefactor=Age 1 FI 1 P/1000000,inwhichAge=pavementageinyears,FI=freezingindex,0Cdays,P=percentsubgradematerialpassingthe0.075mmsieve.EdgeorstructuralpunchoutisamajorstructuraldistressofCRCPcharacterizedfirstbyalossofaggregateinterlockatoneortwocloselyspacedtransversecracksattheedgeofthepavement.Thecrackorcracksbegintofaultandspallslightly,andwiththeapplicationofheavyaxleloadsacrossthiscrackedsection,alongitudinalcrackisformedbetweenthetransversecracks.Asthecracksdeterioratewithtime,thesteelwithintheconcreterapturesandpiecesofconcretepunchdownunderloadintothesubbaseandsubgrade.Thedistressedareaexpandsinsizeto


adjoiningcracksanddevelopsintoalargeareaifleftunchecked(Huang,2004).CRCPpunchoutsareacombinationofrepeatedheavyaxleloads,lossofLTEacrosstwocloselyspacedtransfercracksofwhichcrackwidthisaprimaryfactor,inadequatePCCslabthickness,freemoisturebeneaththeCRCP,erosionofsupportingsubbaseorsubgradematerialalongedgeofCRCPandnegativeslabcurlingandmoisturewarping.PunchoutsreducetheridequalityoftheroadwayandinfluencetheformationofotherCRCPdistresses(AppliedResearchAssociatesInc,2004g).IntheDesignGuide,onemethodforpredictingCRCPperformanceisbasedontheincrementaldevelopmentofpunchoutdistress.Thepredictionofpunchoutdistressisachievedintermsoftheaccumulatedfatiguedamageassociatedwiththeformationofspecificlongitudinalcracksbetweentwocloselyspacedtransversecracks(LaCourseiereetal,1978,Seleznevaetal,2001,Selezneva,2002,Zollingeretal,1990,Darter,1988).ThecalibratedmodelforpunchoutpredictionasafunctionofaccumulatedfatiguedamageduetoslabbendinginthetransversedirectionisgivenasPO

Eqn.4.23WherePO=totalpredictednumberofpunchoutspermileattheendofimonthlyincrement.D=accumulatedfatiguedamageattheendofimonthlyincrement.a, b, c=calibrationconstantsLocalCalibrationApproachCurrenthighwaysaredesignedbasedontypicalhistoricclimaticpatterns,reflectinglocalclimateandincorporatingassumptionsaboutareasonablerangeoftemperaturesandprecipitationlevels.Givenanticipatedclimatechangesandtheinherentuncertaintyassociatedwithsuchchanges,apavementcouldbesubjectedtoverydifferentclimaticconditionsoverthedesignlifeandmightbeinadequatetowithstandfutureclimateforcesthatimposestressesbeyondenvironmentalfactorscurrentlyconsideredinthedesignprocess.TheMEPDGperformancemodelsweredevelopedusinghistoricaldataanddidnttakeclimatechangeintoconsideration.Inaddition,thecoefficientsintheperformancewerebasedonnationalclimatedatasets.Thesenationalcalibrationfactorsmaynotbeappropriateforspecificregionsofthecountrythathavetheirownclimatepatterns.Inordertogeneratemoreaccurateperformancepredictionsforamorerobustpavementdesigninthelightofpotentialclimatechange,theperformancemodelsneedtobelocallycalibratedtoconsidertheimpactofthechange.TheconceptoflocalcalibrationinMEPDGistoeliminatebiasbetweennationalmodelsandlocalconditions,toreducethestandarderrorassociatedwiththepredictionequationsandtoconsiderthedifferencesinmaterials,constructionspecifications,policiesonpavementpreservationandmaintenanceacrossthenation.TheMEPDGsoftwareincorporatesthelocalcalibrationcoefficientsfortheperformancemodelsthatcanbechangedbytheuserstomakeadjustmentstothepredictedperformancevalues.Figure4.1showsascreenshotofthetoolssectionwherethesevaluescanbeenteredintothesoftwareforeachperformanceindicatoronaprojectbasis.Inthisstudy,weexpandthisconcepttolocalclimatechangeconditionsand


applyittoadapttothechangebycalibratingthecoefficientsoftheperformancepredictionmodels.

Figure4.1MEPDGLocalCalibrationScreenShot

OverviewoftheMethodologyTotailordistressestomeetlocalpavementconditions,sensitivityanalysiswasconductedtolocallycalibratedistresses.Subsequentlocalcalibrationanalysisintheresearchproceededbasedonresultsobtainedfromtheparallelcomparisonsbetweenpotentialclimatechangeandnochangestoclimate.Theprocedureoflocalcalibrationisamajoriterativeworkeffort.Thecalibrationprocess,asdeveloped,involvesfivebasicstepsasfollows:

Reviewallinputdata. Conductsensitivityanalysis. Conductcomparativestudies. Conductvalidation/calibrationstudies. Modifyinputdefaultsandcalibrationcoefficientsasneeded.

Step1:ReviewAllInputDataAllinputstotheMEPDGsoftwareshouldbereviewedandthedesiredlevelandproceduresforobtainingeachinputonvarioustypesofdesignprojectsbedetermined.Severalinputsarevery


criticalbutarenotwelldefinedintheMEPDGsoftwareandthesearetheonesthedesignentityshouldconductsensitivityanalysison.Theprocessisasfollows:

DetermineifdefaultsprovidedwiththeMEPDGsoftwareareappropriateforthedesignentityandifnot,modifyasneeded.

Selectallowablerangesforinputsforvarioustypesofprojectswithinthegeographicalareaofthedesigner(lowvolume,highvolume,differentgeographicareaswithinthestate).

Selectprocedurestoobtaintheseinputsforregulardesignprojects(e.g.,trafficvolumeandweightinputs).Determinetheeffectsoftheaccuracyofinputvaluesontheresultingdesign.

Conductnecessarytestingtoestablishspecificinputs(e.g.,materialcharacterization,axleloaddistributions)andacquireneededequipmentforanytestingrequired.

Conductanalysestoestablishthedesiredlevelofdesignreliabilityforvarioustypesofhighways(e.g.,Interstate,primary,secondary)orlevelsoftraffic.

Step2:SensitivityAnalysisThisisaccomplishedbyselectingatypicaldesignsituationwithalldesigninputs.ThesoftwareisrunandthemeandistressesandIRIpredictedoverthedesignperiod.Thenindividualinputsarevariedandthechangeinalloutputsobserved.Appropriatetablesandplotsareprepared,theresultsevaluated,andinputsdividedintogroupsbasedontheirsensitivitytooutputs,suchasthosethathaveverysignificanteffect,amoderateeffect,andonlyminoreffect.Thoseinputsthathavesignificantimpactsmustbeselectedmorecarefullythanthosewithminoreffects.Theabovesensitivitymayberepeatedforlow,mediumandhightrafficprojectdesignstoseeifthathasaneffectoninputs.Step3:ComparativeStudiesConductingcomparativestudiesusingtheMEPDGsoftwarecanprovideobservationsofvariousdesigninputsonpavementperformance.Inthisstudy,thecomparisonanalysesareconductedtoexaminehowtheclimatechangevariabilitymightaffecttheperformanceofpavementsectionsovertime.Thisinvolvedcomparingtheperformancedeteriorationsoftwoparalleldesigns,onewhichconsideredtheimpactsofclimatechangewithitsdifferentscenariosandonewhichdidnotconsiderclimatechange.Step4:CalibrationtoLocalConditionsAvalidationprocessshouldbedevelopedtoconfirmthatthenationalcalibrationfactorsorfunctionsareadequateandappropriatefortheconstruction,materials,climate,traffic,andotherconditionsthatareencounteredwithinthedesignershighwaysystem.Prepareadatabaseofagencyperformancedataandcomparethedesignresultswiththeperformanceoftheselocalsections.Thiswillrequirecomprehensiveexperimentaldesignandtheselectionofastatisticallysufficientnumberofpavementsectionsforanalysis.Thegoalofthecalibration


validationprocessistoconfirmthattheperformancemodelsaccuratelypredictpavementdistressandridequalityonanationalbasis.Foranyspecificgeographicarea,adjustmentstothenationalmodelsmaybeneededtoobtainreliablepavementdesigns.Step5:ModifytheCalibrations/InputsIfsignificantdifferencesarefoundbetweenthepredictedandmeasureddistressesandIRIfortheagencieshighways,appropriateadjustmentsmustbemadetothecalibrationcoefficients.Makemodificationstothedefaultnationalcoefficientsintheperformancemodelsasneededbasedonalloftheaboveresultsandfindings.Theseresultscouldthenbeusedtoestablishanewstandarddeviationmodelforuseinreliabilitydesigntoprovideamorecosteffectivedesign.


5. CaseStudyandImplementationStudySitesandPavementStructuresThepotentialimpactsofclimatechangeanditsuncertaintyonpavementperformanceanddesignwereexploredusingsitesintheNorthEasternregionoftheUnitedStatesasthereferenceareaofstudy.Threestates,namelyDelaware,NewJerseyandConnecticut,wereselectedwithinthestudyregionandflexibleandrigidpavementtypeswerechosenforexperimentaldesigns.Eachofthepavementlocationshadclimateconditionspeculiartothelocationandtheseconditionsformedtheplatformfromwhichexpectationswithrespecttofutureclimatechangesweremade.Pavementtypesanalyzedwereasphalticconcretepavement,continuouslyreinforcedconcretepavement(CRCP)andjointedplainconcretepavement(JPCP).Foreachpavementtypeandaspecificlocation,anexistingLongTermPavementPerformance(LTPP)pavementsectionwasidentifiedanditscharacteristicssuchaspavementstructure,trafficinformationandlayermaterialpropertieswereusedasinputindevelopingexperimentalunitsforthestudy.Assuch,theasphaltconcretepavementusedinthisresearchwasareplicaofInterstate95inNewJersey,theexperimentaldesignforCRCPwasbasedonInterstate495inDelawareandthatforJPCPfollowedtherigidsectionofInterstate84WinConnecticut.PavementstructuresforallthesehighwaysweredesignedusinginformationfromtheLongTermPavementPerformance(LTPP)database.Thissectiondescribesthedevelopmentofpavementstructuresforthestudy.Thestructureoftheasphaltconcretepavementconsistedoftwolayers:anasphaltlayerandanunboundgranularbase,placedontopofanexistingsubgrade.TheJPCPwasmadeupofaPortlandconcretelayerandagranularbaselayerontopofitssubgrade.ThestructureforCRCPconsistedthreeconstructedlayersinadditiontothesubgrade.Theadditionallayerswereanunboundsubbase,atreatedbaseandaPortlandconcretelayerinascendingorder.ThicknessesforeachlayerwiththeexceptionofthesubgradewereprovidedintheLTPPdatabaseandwereusedforinitialperformancerunsinMEPDG.AlsocontainedintheLTPPdatabaseweretheconstituentmaterialsofthelayersandtheirrespectivepropertiesandcharacteristics.Thelocations,pavementtypes,LTPPstructures,andadjustedMEPDGdesignsforthethreetestsitesareincludedinTable5.1.GivenLTPPsectionsweredesignedusingtheAASHTOGuideforDesignofPavementStructureandrecognizingthatthesestructuresaremoreconservativethanthosedesignedusingtheMEPDGsoftware,thestructuraldesignsforthestudywereadjustedwherenecessary.Thiswasdoneasfollows:iftheAASHTOdesignpassedalltheMEPDGperformancecriteriarequirements,thesurfacelayerthicknesswasreducedinincrementsofhalfaninchandMEPDGanalysiswasperformed.Thisprocesswasrepeateduntiloneoftheperformancecriteriafailed,thentheMEPDGdesignthicknesswasthatthicknessplus0.5inches.OntheotherhandiftheAASHTOdesignfailed,analysisstartedwithanincreaseofthethicknessbyhalfaninchandfollowedthesamephilosophydescribedabovetoachieveanacceptableMEPDGdesign.


Table5.1TestSitesoftheCaseStudyStateID

SHRPID Route Type

LTPPStructure Lat Long

Elevation(ft)

MEPDGAdjustedStructure

NJ34 6057 I95 AC 40.27 74.83 222

CT09 4008 I84W JPCP 41.80 72.56 155

DE10 5004 I495 CRCP 39.74 75.51 14

Note:ACAsphaltConcrete;PCPortlandConcrete;GBgranularbase;SSsandsoil;TBboundtreatedbase;GSunboundgranularsubbase.HistoricalClimaticDataForanyprojectedchangesinclimatetobemade,ahistoryofclimaticdatawasfirstexaminedforthethreetestsites.TheclimaticdatausedinMEPDGwasobtainedfromadatabasemanagedbytheNationalClimaticDataCenterwhichcontainsrecordsforlocationsalloverthecountry.Forthethreetestsites,themostappropriateweatherstationswerethefollowingstations:BradleyInternationalAirportinConnecticut(stationID14740)fortheJPCPsection,NewCastleCountyAirportinDelaware(stationID13781)fortheCRCPandTrento

cambio climatico1

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